The dry basis elemental composition of the feedstock, shown in Table 2, is identical to previous NREL and PNNL design reports [20,21]. The composition was originally assumed to come from pulpwood. Recent feedstock logistics work at the Idaho National Laboratory (INL) suggests that the use of blended material may be required to meet a cost target of $80/dry U.S. ton while still meeting these specifications [22]. For the purpose of this report, it is assumed that any blended material provided to meet this feedstock elemental composition will not adversely affect fast pyrolysis conversion efficiencies. Ongoing studies being conducted jointly by INL, NREL, and PNNL will provide experimental evidence of the impact of blended feedstocks on fast pyrolysis and gasification processes. Future TEA will be modified to reflect conversion impacts inferred from such studies.This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. not considered in this design in order to focus on the core technology of in situ and ex situ fast pyrolysis vapor upgrading. Aspen Plus ModelAn Aspen Plus Version 7.2 simulation was used as the basis for this report. Since the products in pyrolysis are numerous and varied, only selected model compounds were used to represent the product slate. Additional hydrocarbon species were added to represent hydroprocessing products. Many of the desired molecular species in the desired boiling ranges for light and heavy fractions did not exist in Aspen Plus databanks and physical property parameters needed to be estimated. The biomass feedstock, ash, char, and coke were modeled as non-conventional components. Appendix F provides information about compounds selected to represent the process. The Peng-Robinson with Boston-Mathias modifications (PR-BM) equation of state was used throughout most of the process simulation. The ASME 1967 steam table correlations (STEAM-TA) were used for the steam cycle calculations. Combustor/Regenerator Temperature, °C (°F) 650 (1,202) 720 (1,328) 650 (1,202) Pressure, psia (bar) 117 (8.1) 117 (8.1) 113 (7.8) Excess air (%) 20 20 20 Solids temperature before transfer to reactor, °C (°F) 650 (1,202) 720 (1,328) 341 (645) No. of cyclones per combustor 2 2 2 Area 200 Equipment Cost EstimationsCapital costs for the equipment in this area were estimated by Harris Group. A previously developed spreadsheet tool for gasifier costs was leveraged for this exercise. Cost estimates from this tool were compared with order of magnitude estimates from technology vendors and documented in Appendix I of Worley et al.

Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide and is heterogeneous both morphologically and molecularly. In an era of personalized medicine, the greatest challenge is to predict individual response to therapy and distinguish patients likely to be cured with surgical resection of tumors and systemic therapy from those resistant or non-responsive to treatment. Patients would avoid futile treatments, including clinical trial regimes and ultimately this would prevent under- and over-treatment and reduce unnecessary adverse side effects. In this review, the potential of specific biomarkers will be explored to address two key questions—1) Can the prognosis of patients that will fare well or poorly be determined beyond currently recognized prognostic indicators? and 2) Can an individual patient’s response to therapy be predicted and those who will most likely benefit from treatment/s be identified? Identifying and validating key prognostic and predictive biomarkers and an understanding of the underlying mechanisms of drug resistance and toxicity in CRC are important steps in order to personalize treatment. This review addresses recent data on biological prognostic and predictive biomarkers in CRC. In addition, patient cohorts most likely to benefit from currently available systemic treatments and/or targeted therapies are discussed in this review.

Colorectal surgery was generally safe for nonagenarians in this study. This study demonstrates that excellent outcomes can be achieved in a selected group. Additional prospective studies with larger numbers and 5-year follow-up are recommended.